Functional Brain Networks Are Dominated by Stable Group and Individual Factors, Not Cognitive or Daily Variation

Neuron, Год журнала: 2018, Номер 98(2), С. 439 - 452.e5

Опубликована: Апрель 1, 2018

Язык: Английский

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Brain network dynamics are hierarchically organized in time

Proceedings of the National Academy of Sciences, Год журнала: 2017, Номер 114(48), С. 12827 - 12832

Опубликована: Окт. 30, 2017

The brain recruits neuronal populations in a temporally coordinated manner task and at rest. However, the extent to which large-scale networks exhibit their own organized temporal dynamics is unclear. We use an approach designed find repeating network patterns whole-brain resting fMRI data, where are defined as graphs of interacting areas. that transitions between nonrandom, with certain more likely occur after others. Further, this nonrandom sequencing itself hierarchically organized, revealing two distinct sets networks, or metastates, has tendency cycle within. One metastate associated sensory motor regions, other involves areas related higher order cognition. Moreover, we proportion time subject spends each consistent subject-specific measure, heritable, shows significant relationship cognitive traits.

Язык: Английский

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Towards a Universal Taxonomy of Macro-scale Functional Human Brain Networks

Brain Topography, Год журнала: 2019, Номер 32(6), С. 926 - 942

Опубликована: Ноя. 1, 2019

Язык: Английский

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Questions and controversies in the study of time-varying functional connectivity in resting fMRI

Network Neuroscience, Год журнала: 2019, Номер 4(1), С. 30 - 69

Опубликована: Дек. 16, 2019

The brain is a complex, multiscale dynamical system composed of many interacting regions. Knowledge the spatiotemporal organization these interactions critical for establishing solid understanding brain's functional architecture and relationship between neural dynamics cognition in health disease. possibility studying through careful analysis neuroimaging data has catalyzed substantial interest methods that estimate time-resolved fluctuations connectivity (often referred to as "dynamic" or time-varying connectivity; TVFC). At same time, debates have emerged regarding application TVFC analyses resting fMRI data, about statistical validity, physiological origins, cognitive behavioral relevance TVFC. These other unresolved issues complicate interpretation findings limit insights can be gained from this promising new research area. This article brings together scientists with variety perspectives on review current literature light issues. We introduce core concepts, define key terms, summarize controversies open questions, present forward-looking perspective how rigorously productively applied investigate wide range questions systems neuroscience.

Язык: Английский

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Resting brain dynamics at different timescales capture distinct aspects of human behavior

Nature Communications, Год журнала: 2019, Номер 10(1)

Опубликована: Май 24, 2019

Abstract Linking human behavior to resting-state brain function is a central question in systems neuroscience. In particular, the functional timescales at which different types of behavioral factors are encoded remain largely unexplored. The counterparts static connectivity (FC), resolution several minutes, have been studied but correlates dynamic measures FC few seconds unclear. Here, using fMRI and 58 phenotypic from Human Connectome Project, we find that captures task-based phenotypes (e.g., processing speed or fluid intelligence scores), whereas self-reported loneliness life satisfaction) equally well explained by FC. Furthermore, behaviorally relevant emerges interconnections across all networks, rather than within between pairs networks. Our findings shed new light on cognitive processes involved distinct facets behavior.

Язык: Английский

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The behavioral and cognitive relevance of time-varying, dynamic changes in functional connectivity

NeuroImage, Год журнала: 2017, Номер 180, С. 515 - 525

Опубликована: Сен. 21, 2017

Язык: Английский

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High-amplitude cofluctuations in cortical activity drive functional connectivity

Proceedings of the National Academy of Sciences, Год журнала: 2020, Номер 117(45), С. 28393 - 28401

Опубликована: Окт. 22, 2020

Significance Despite widespread applications, the origins of functional connectivity remain elusive. Here we analyze human neuroimaging data. We decompose resting-state across time to assess contributions moment-to-moment activity cofluctuations overall pattern. show that is driven by a small number high-amplitude frames. these frames are underpinned specific mode brain activity; topography this gets modulated during in-scanner tasks; and encode personalized, subject-specific information. In summary, our parameter-free method provides an exact mathematical link between frame-wise cofluctuations, creating opportunities for studying both static time-varying networks.

Язык: Английский

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Metastable brain waves

Nature Communications, Год журнала: 2019, Номер 10(1)

Опубликована: Март 5, 2019

Abstract Traveling patterns of neuronal activity—brain waves—have been observed across a breadth recordings, states awareness, and species, but their emergence in the human brain lacks firm understanding. Here we analyze complex nonlinear dynamics that emerge from modeling large-scale spontaneous neural activity on whole-brain network derived tractography. We find rich array three-dimensional wave patterns, including traveling waves, spiral sources, sinks. These are metastable, such multiple spatiotemporal visited sequence. Transitions between correspond to reconfigurations underlying phase flows, characterized by instabilities. metastable accord with empirical data imaging modalities, electrical waves cortical tissue, sequential resting-state MEG data, electrocorticography. By moving study functional networks spatially static an inherently dynamic (wave-like) frame, our work unifies apparently diverse phenomena neuroimaging modalities makes specific predictions for further experimentation.

Язык: Английский

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Dynamics of large-scale electrophysiological networks: A technical review

NeuroImage, Год журнала: 2017, Номер 180, С. 559 - 576

Опубликована: Окт. 10, 2017

Язык: Английский

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Replicability of time-varying connectivity patterns in large resting state fMRI samples

NeuroImage, Год журнала: 2017, Номер 163, С. 160 - 176

Опубликована: Сен. 13, 2017

The past few years have seen an emergence of approaches that leverage temporal changes in whole-brain patterns functional connectivity (the chronnectome). In this chronnectome study, we investigate the replicability human brain's inter-regional coupling dynamics during rest by evaluating two different dynamic network (dFNC) analysis frameworks using 7 500 magnetic resonance imaging (fMRI) datasets. To quantify extent to which emergent (FC) are reproducible, characterize deriving several summary measures across multiple large, independent age-matched samples. Reproducibility was demonstrated through existence basic (FC states) amidst ensemble connections. Furthermore, application methods conservatively configured (statistically stationary, linear and Gaussian) surrogate datasets revealed some studied state were indeed statistically significant also suggested class null model did not explain fMRI data fully. This extensive testing reproducibility similarity statistics suggests estimated FC states robust against variation quality, analysis, grouping, decomposition methods. We conclude future investigations probing neurophysiological relevance time-varying assume critical importance.

Язык: Английский

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